Sensor devices can infer biometrics of interest from sensor data that are associated with activities of a user. In many implementations of sensor devices, however, the high accuracy of biometric estimates is achieved by limiting activity types and/or activity intensities that the sensor devices can monitor. For example, pedometers are recommended to be worn on the left mid-axillary position for the most accurate step counts (Horvath et al. 2007). Even with the ideal placement location, pedometers can fail to provide reliable step counts, either by overcounting or undercounting steps in some activities such as bus riding.
The placement of sensor devices is a significant constraint. Users of sensor devices prefer to wear their portable sensor devices in convenient locations. However, these convenient locations are often not ideal for collecting biometric data. For example, the location of the sensor device may be remote from the body part or body parts that are mainly involved in the activity or have the strongest biometric signal. For this reason, current sensor devices sacrifice convenience for accuracy or vice versa.
Recent advances in sensor, electronics, and power source miniaturization have allowed the size of personal health monitoring devices, also referred to herein as “biometric tracking” or “biometric monitoring” devices, to be offered in small sizes. These biometric monitoring devices may collect, derive, and/or provide one or more of the following types of information: step counts, ambulatory speed, distance traveled cadence, heart rate, calorie burn, floors climbed and/or descended, location and/or heading, elevation, etc. However, the miniature size of the product limits the electric power it supplies. Therefore, there is the need for energy saving methods and hardware that allow high speed and accurate computation of biometric information.
The inventions disclosed herein enable sensor devices to use one or more modes to achieve computation speed and accuracy while maintaining energy efficiency.